Interpretation des predictions appartements
Author : VotreNom
Description : Rapport Shapash pour appartements
Project_Name : Analyse extratrees_appart
Model used : ExtraTreesRegressor
Library : sklearn.ensemble._forest
Library version : 1.5.2
Model parameters :
| Parameter key | Parameter value |
|---|---|
| estimator | ExtraTreeRegressor() |
| n_estimators | 254 |
| estimator_params | ('criterion', 'max_depth', 'min_samples_split', 'min_samples_leaf', 'min_weight_fraction_leaf', 'max_features', 'max_leaf_nodes', 'min_impurity_decrease', 'random_state', 'ccp_alpha', 'monotonic_cst') |
| bootstrap | False |
| oob_score | False |
| n_jobs | None |
| random_state | None |
| verbose | 0 |
| warm_start | False |
| class_weight | None |
| max_samples | None |
| criterion | squared_error |
| max_depth | 20 |
| min_samples_split | 5 |
| Parameter key | Parameter value |
|---|---|
| min_samples_leaf | 1 |
| min_weight_fraction_leaf | 0.0 |
| max_features | 1.0 |
| max_leaf_nodes | None |
| min_impurity_decrease | 0.0 |
| ccp_alpha | 0.0 |
| monotonic_cst | None |
| feature_names_in_ | ['etage' 'surface' 'nb_pieces' 'balcon' 'eau' 'bain' 'dpeL' 'dpeC' 'mapCoordonneesLatitude' 'mapCoordonneesLongitude' 'annonce_exclusive' 'nb_etages' 'places_parking' 'cave' 'ges_class' 'annee_construction' 'nb_toilettes' 'ascenseur' 'nb_logements_copro' 'charges_copro' 'chauffage_energie' 'chauffage_systeme'... |
| n_features_in_ | 56 |
| _n_samples | 11035 |
| n_outputs_ | 1 |
| _n_samples_bootstrap | None |
| estimator_ | ExtraTreeRegressor() |
| estimators_ | [ExtraTreeRegressor(max_depth=20, min_samples_split=5, random_state=1936962966), ExtraTreeRegressor(max_depth=20, min_samples_split=5, random_state=2069891226), ExtraTreeRegressor(max_depth=20, min_samples_split=5, random_state=2018050919), ExtraTreeRegressor(max_depth=20, min_samples_split=5,... |
| Training dataset | Prediction dataset | |
|---|---|---|
| number of features | NaN | 56 |
| number of observations | NaN | 2,759 |
| missing values | NaN | 0 |
| % missing values | NaN | 0 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 135 |
| std | 78.3 |
| min | 0 |
| 25% | 58 |
| 50% | 140 |
| 75% | 204 |
| max | 289 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | -0.0126 |
| std | 0.998 |
| min | -1.2 |
| 25% | -0.625 |
| 50% | -0.341 |
| 75% | 0.458 |
| max | 3.92 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 0.0367 |
| std | 0.994 |
| min | -2.12 |
| 25% | -0.332 |
| 50% | 0.109 |
| 75% | 1 |
| max | 1 |
| Prediction dataset | |
|---|---|
| distinct values | 5 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 5 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | -0.0232 |
| std | 1.01 |
| min | -6.43 |
| 25% | -0.53 |
| 50% | -0.079 |
| 75% | 0.755 |
| max | 1.35 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 4 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 5 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 3 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | -0.0406 |
| std | 0.939 |
| min | -1.97 |
| 25% | -0.123 |
| 50% | -0.123 |
| 75% | -0.123 |
| max | 8.65 |
| Prediction dataset | |
|---|---|
| distinct values | 4 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 3 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 4 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 0.0292 |
| std | 1.02 |
| min | -1.79 |
| 25% | -0.672 |
| 50% | -0.157 |
| 75% | 0.625 |
| max | 8.62 |
| Prediction dataset | |
|---|---|
| distinct values | 7 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 4 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | -0.0135 |
| std | 0.976 |
| min | -0.514 |
| 25% | -0.514 |
| 50% | -0.155 |
| 75% | 0.205 |
| max | 17.5 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 8 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 8 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 0.00369 |
| std | 0.983 |
| min | -1.75 |
| 25% | -0.499 |
| 50% | -0.301 |
| 75% | 0.681 |
| max | 2.74 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | -0.00558 |
| std | 0.975 |
| min | -3.59 |
| 25% | -0.413 |
| 50% | -0.157 |
| 75% | 0.358 |
| max | 1.97 |
| Prediction dataset | |
|---|---|
| distinct values | 6 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 0.00533 |
| std | 0.919 |
| min | -0.612 |
| 25% | -0.263 |
| 50% | -0.233 |
| 75% | -0.188 |
| max | 14.5 |
| Prediction dataset | |
|---|---|
| distinct values | 9 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 4 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 2 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 0.0215 |
| std | 1.01 |
| min | -0.896 |
| 25% | -0.815 |
| 50% | -0.654 |
| 75% | 0.992 |
| max | 1.52 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 0.00312 |
| std | 1.01 |
| min | -2.18 |
| 25% | -0.732 |
| 50% | 0.173 |
| 75% | 0.394 |
| max | 7.58 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 0.021 |
| std | 1.01 |
| min | -0.903 |
| 25% | -0.823 |
| 50% | -0.628 |
| 75% | 0.965 |
| max | 1.53 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | -0.000406 |
| std | 0.98 |
| min | -2.36 |
| 25% | -0.659 |
| 50% | 0.228 |
| 75% | 0.713 |
| max | 6.05 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 0.00801 |
| std | 0.994 |
| min | -0.901 |
| 25% | -0.769 |
| 50% | -0.606 |
| 75% | 0.418 |
| max | 2.01 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | -0.0118 |
| std | 0.963 |
| min | -0.439 |
| 25% | -0.351 |
| 50% | -0.285 |
| 75% | -0.0617 |
| max | 10.2 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 0.0223 |
| std | 1.01 |
| min | -0.88 |
| 25% | -0.806 |
| 50% | -0.675 |
| 75% | 1.03 |
| max | 1.51 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | -0.00618 |
| std | 0.999 |
| min | -2.36 |
| 25% | -0.717 |
| 50% | -0.173 |
| 75% | 0.348 |
| max | 3.79 |
| Prediction dataset | |
|---|---|
| distinct values | 1 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 1 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| distinct values | 8 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 0.0219 |
| std | 0.989 |
| min | -2.16 |
| 25% | -0.327 |
| 50% | 0.0367 |
| 75% | 0.136 |
| max | 7.12 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 0.0239 |
| std | 1.01 |
| min | -0.919 |
| 25% | -0.813 |
| 50% | -0.608 |
| 75% | 0.735 |
| max | 1.65 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | -0.0144 |
| std | 0.982 |
| min | -2.76 |
| 25% | -0.875 |
| 50% | 0.21 |
| 75% | 0.839 |
| max | 3.1 |
| Prediction dataset | |
|---|---|
| distinct values | 3 |
| missing values | 0 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | -0.0223 |
| std | 0.993 |
| min | -2.08 |
| 25% | -0.606 |
| 50% | -0.148 |
| 75% | 0.408 |
| max | 9.2 |
| Prediction dataset | |
|---|---|
| count | 2,759 |
| mean | 2,550 |
| std | 1,070 |
| min | 216 |
| 25% | 1,710 |
| 50% | 2,440 |
| 75% | 3,300 |
| max | 7,440 |
Note : the explainability graphs were generated using the test set only.
| True values | Prediction values | |
|---|---|---|
| count | 2,759 | 2,759 |
| mean | 2,550 | 2,560 |
| std | 1,070 | 891 |
| min | 216 | 481 |
| 25% | 1,710 | 1,850 |
| 50% | 2,440 | 2,440 |
| 75% | 3,300 | 3,180 |
| max | 7,440 | 7,020 |
MAE : 347
R2 : 0.778
MSE : 256,000
MAPE : 0.172
MdAE : 234
Explained Variance : 0.778